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Record W4386572870 · doi:10.1177/23333936231193885

The Social Relations of Ethnographic Fieldwork: Access, Ethics and Research Governance

2023· article· en· W4386572870 on OpenAlexaff
Shobha Nepali, Rochelle Einboden, Trudy Rudge

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsEthnographyCorporate governanceSociologyResearch ethicsEngineering ethicsPolitical sciencePublic relationsAnthropologyBusinessEngineering

Abstract

fetched live from OpenAlex

The focus of this methodological paper is to discuss the challenges of conducting fieldwork, using reflections from our experiences of accessing a research site for ethnographic data collection. The research project aimed to explore nurses' social relations in their workplace and the inequities between and within these relations among nurses of diverse social positions. Due to the sensitive nature of this topic, access to the research site posed several challenges and was further complicated by the bureaucratic ethics process that governs clinical sites in Australia. Although this study was considered a low and negligible risk research, negotiating the ethics process was full of hitches and hindrances resulting in the refusal of access. This paper offers ethnographers a reflection on challenges in accessing clinical sites to conduct research and a discussion of strategies that may be useful to navigate and counter these challenges by managing social relations in the field.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.176
metaresearch head score (Gemma)0.163
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.932

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1760.163
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0160.054
Scholarly communication0.0170.012
Open science0.0020.014
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.753
GPT teacher head0.757
Teacher spread0.004 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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